Beyond the era of biotechnology lies the era of pervasive computation and advanced nanotechnology, starting around 2030, I would imagine. Processing cycles will be ten thousand times more abundant than now and applications of molecular manufacturing will be tentatively emerging from the labs. This is the era in which the human brain will be reverse-engineered, the first strong artificial intelligences constructed, and perhaps most importantly, inroads made into the grail of radical life extension: incrementally replacing the biology of the brain with something more robust and damage-resistant.
I would get my neurons replaced (slowly, one at a time over time, to ensure continuity of the self) with some form of much more robust, easily maintained nanomachinery. That allows these sorts of engineering possibilities:
- Swapping out the body for whatever machinery of transport and support best minimizes risk
- Moving most of the business of life into simulation
- Physically separating my neurons while still remaining alive, conscious and active
It's that last point that's key, as physical locations have the same sort of issues with time, probability and bad events as people do. Meteorites happen, as do landslides, earthquakes and volcanoes. The way to reduce your risk function dramatically is to spread out. You can imagine a wireless brain (using whatever the most robust communications technology of the time happens to be be) scattered in a thousand separate locations across a continent, or the whole planet.
I notice that the Future of Humanity Institute has published a (PDF) roadmap to whole brain emulation (WBE) - a tiny step towards the visions outlined above. In intent it could be compared to SENS, or the work of Drexler, Freitas and others on the design of medical nanomachinery: a foundation of theory on which research strategies can be built.
As this review shows, WBE on the neuronal/synaptic level requires relatively modest increases in microscopy resolution, a less trivial development of automation for scanning and image processing, a research push at the problem of inferring functional properties of neurons and synapses, and relatively business‐as‐usual development of computational neuroscience models and computer hardware.
This assumes that this is the appropriate level of description of the brain, and that we find ways of accurately simulating the subsystems that occurs on this level. Conversely, pursuing this research agenda will also help detect whether there are low‐level effects that have significant influence on higher level systems, requiring an increase in simulation and scanning resolution.
There do not appear to exist any obstacles to attempting to emulate an invertebrate organism today. We are still largely ignorant of the networks that make up the brains of even modestly complex organisms. Obtaining detailed anatomical information of a small brain appears entirely feasible and useful to neuroscience, and would be a critical first step towards WBE. Such a project would serve as both a proof of concept and test bed for further development.
If WBE is pursued successfully, at present it looks like the need for raw computing power for real‐time simulation and funding for building large‐scale automated scanning/processing facilities are the factors most likely to hold back large‐scale simulations.